Evidence map›Paper›PMID 41970567›Full record

ArticleBiomedical optics express2026

Highly parallel, 1060 nm interferometric diffusing wave spectroscopy with a time-of-flight filter.

Santosh Aparanji, Mingjun Zhao, Akshay Shashidhar Nadig, Hector Garcia Estrada, Drew Hamilton, Vivek J Srinivasan

Abstract read
In one paragraph

Article in Biomedical optics express, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Santosh AparanjiTech4Health Institute, NYU Langone Health, New York, New York 11101, USA.ORCID https://orcid.org/0009-0004-2459-4322
Mingjun ZhaoTech4Health Institute, NYU Langone Health, New York, New York 11101, USA.ORCID https://orcid.org/0000-0002-8657-4413
Akshay Shashidhar NadigTech4Health Institute, NYU Langone Health, New York, New York 11101, USA.
Hector Garcia EstradaTech4Health Institute, NYU Langone Health, New York, New York 11101, USA.
Drew HamiltonTech4Health Institute, NYU Langone Health, New York, New York 11101, USA.
Vivek J SrinivasanTech4Health Institute, NYU Langone Health, New York, New York 11101, USA.ORCID https://orcid.org/0000-0001-9683-1949

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interferometric diffuse optics (iDO) has recently emerged as a promising class of near-infrared (NIR) light technologies for monitoring human brain signals associated with coherent light fluctuations. In this work, we demonstrate a line scan interferometric diffusing wave spectroscopy (iDWS) system at 1060 nm, a wavelength that has a multitude of benefits for high-speed cerebral blood flow index (BFI) monitoring. Pulsatile BFI measurements on the forehead of a moderately dark-skinned (Fitzpatrick Type V) subject with medium-length black hair up to a source-collector (S-C) separation of 5.5 cm on the forehead and 4.0 cm over the parietal cortex are demonstrated in continuous wave (CW) mode. On this high-throughput platform, we further implement a simple time-of-flight filter (TOF) via source wavelength tuning. The TOF filter can be turned on and off, and its width can be changed electronically, enabling probing different sample depths without requiring multiple S-C separations. At 4 cm S-C separation, an electronic TOF filter afforded a 2.92-fold reduction in scalp sensitivity over CW mode. With further optimization, the combination of TOF filtering with highly parallel detection in the 1060 nm range promises to improve depth sensitivity and signal-to-noise ratio of iDO in neuromonitoring applications.

Identifiers

PMID41970567
PMCPMC13064615

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.